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AI Engineer with 2+ years in GenAI & LLM Systems and Full-Stack Integration
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AI/ML Engineer with 2+ years of hands-on experience building and deploying production GenAI systems RAG pipelines, LLM-powered applications, NLP, and conversational AI with complete ownership across design, integration, and cloud deployment on AWS EC2. Grounded in ECE systems thinking, I bring a sharp eye for scalability and performance to every solution I build. My next goal is clear: contribute to innovative, high-impact AI products alongside teams that are serious about pushing GenAI to its full potential.
Nadimpalli Satyanarayana Raju Institute of Technology (JNTU-GV)
B.Tech · Electronics & Communication Engineering
August 1, 2019 – June 30, 2023
Work Nexus Data Solutions
Software Engineer (AI/ML Focus)
April 1, 2026 – Present
Visakhapatnam, Andhra Pradesh, India
Work Nexus Data Solutions
Frontend Developer
September 1, 2025 – April 1, 2026
Visakhapatnam, Andhra Pradesh, India
Nexii IT Labs
Frontend Developer
December 1, 2024 – August 1, 2025
Visakhapatnam, Andhra Pradesh, India
Nexii IT Labs
Frontend Developer Intern
October 1, 2024 – November 1, 2024
Visakhapatnam, Andhra Pradesh, India
TRIBN Software Solutions
Web Developer Intern
February 1, 2024 – August 1, 2024
Hyderābād, Telangana, India
GenAI Resume Assistant - Production RAG Pipeline
June 24, 2026 – Present
Built a production-grade RAG pipeline using LangChain, ChromaDB vector storage, and Gemini 2.5 Flash inference achieving hallucination-free Q&A by enforcing zero-temperature constraints and top-k semantic retrieval over ingested PDF corpora. Generated multi-dimensional vector embeddings with Ollama nomic-embed-text model, persisting indices into ChromaDB for rapid similarity-based top-k text fragment retrieval.
View ProjectEnterprise Salary Prediction Pipeline
June 24, 2026 – Present
Achieved 97% accuracy on unseen test data using a Scikit-learn pipeline with StandardScaler, OneHotEncoder, and Random Forest, trained on a strict 70/15/15 data split with log-transformation for right-skewed targets.
WhatsApp Marketing Automation Engine
June 24, 2026 – Present
Reduced campaign hard-fail rate to under 2% across 12,500+ lead records by engineering webhook event handlers with anti-spam AI guardrails, automated failure-pause logic, and a global 48-hour cooldown enforcement system deployed in production with zero manual intervention. Designed a rule-bound AI state machine (IntentConfig, IntentTransition, Lead) with Celery-beat scheduling to autonomously execute multi-tier campaign sequences. Integrated Sarvam AI NLP models for real-time Hindi-to-English text translation, transliteration, and audio transcription within the automated AI communication pipeline.
Meta Ads AI Automation Platform
June 24, 2026 – Present
Engineered an AI-driven programmatic advertising platform with rule-based ML decision logic for automated day-parting schedules, dynamic budget allocation, and precision geographic/demographic targeting. Developed a server-side generative content pipeline (Pillow, MoviePy) to programmatically produce AI-enriched marketing images and promotional videos with automated branding overlays. Implemented a low-latency Lead Ads webhook-to-CRM pipeline with Celery-based 15-minute polling safety net ensuring 100% payload capture and data synchronization integrity. Managed end-to-end AWS EC2 deployment with Nginx reverse proxy, TLS/SSL, WebSocket support, and systemd process supervision.
BharatCV.AI — Voice-First Conversational AI Resume Platform
June 24, 2026 – Present
Architected a browser-based speech AI interface integrating Sarvam AI TTS/STT/NLP models with Media Recorder API and client-side FFmpeg (WASM) for real-time WebM-to-WAV audio transcoding and NLP processing. Engineered an AI document compiler using jsPDF and html2pdf.js to map structured NLP-extracted conversational data into standardized, multi-template ATS-compliant resumes automatically. Integrated a JsSIP WebSocket click-to-call system with Asterisk PBX, implementing dynamic number masking to enhance user privacy and communication security.
HiringHero.ai - GenAI Enterprise Talent Acquisition System
June 24, 2026 – Present
Cut manual screening effort by 70% by integrating DeepSeek LLM inference pipelines to auto-generate role-specific technical screening questions and skill-translation prompts dynamically mapped to uploaded job descriptions. Engineered low-latency Redux/Axios state management to ingest indexed candidate profiles from Elasticsearch and run AI-powered applicant-to-JD semantic matching routines. Developed the core AI orchestration UI 'The Arena' managing end-to-end screening workflows: automated tracking, AI-assisted profile review, and identity verification pipelines. Configured real-time candidate analytics dashboards (Chart.js, Recharts), session management and AI-triggered notifications.
Customer Churn Detection System
June 24, 2026 – Present
Resolved 85:15 class imbalance using oversampling, boosting minority-class recall from 43% to 71%; evaluated Gradient Boosting and Random Forest with Scikit-learn feature importance scoring.
Campus Placement Prediction Model
June 24, 2026 – Present
Built an SVM classification model achieving 91.5% F1-score via Stratified K-Fold Cross-Validation on multi-type academic profile data.
LangBot - Documentation-Based RAG Chatbot
June 24, 2026 – Present
Built a production-grade RAG chatbot using LangChain, FAISS vector storage, and Gemini 2.5 Flash to answer natural-language questions over LangChain documentation deployed as a Docker-containerized cloud web service on Render. Engineered a document ingestion pipeline to chunk documentation into vector embeddings; optimized retrieval by restricting searches to topic-specific metadata, reducing token usage and improving response relevance. Designed an interactive Streamlit interface with dynamic topic discovery, citation-based answer display, and source-document visibility for full retrieval transparency.
Cultural Fit Analysis
The candidate's project portfolio is diverse, spanning marketing automation, talent acquisition, conversational AI, and predictive analytics, indicating a broad interest and ability to apply AI in various domains. The focus on 'high-impact AI products' aligns well with an innovative, product-driven culture. The self-taught transition into AI/ML and continuous upskilling beyond academic curriculum suggest a proactive and growth-oriented mindset, which is a strong cultural fit for dynamic tech environments.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and self-learning capabilities, transitioning from an ECE background to AI/ML. Project descriptions highlight problem-solving, ownership (design, integration, deployment), and a focus on scalability and performance. The professional experience shows a progression from Frontend Developer to Software Engineer (AI/ML Focus), indicating adaptability and a clear career trajectory towards AI/ML.